Sunscreens - Which and what for?

It is well established that sun exposure is the main cause for the development of skin cancer. Chronic continuous UV radiation is believed to induce malignant melanoma, whereas intermittent high-dose UV exposure contributes to the occurrence of actinic keratosis as precursor lesions of squamous cell carcinoma as well as basal cell carcinoma. Not only photocarcinogenesis but also the mechanisms of photoaging have recently become apparent. In this respect the use of sunscreens seemed to prove to be more and more important and popular within the last decades. However, there is still inconsistency about the usefulness of sunscreens. Several studies show that inadequate use and incomplete UV spectrum efficacy may compromise protection more than previously expected. The sunscreen market is crowded by numerous products. Inorganic sunscreens such as zinc oxide and titanium oxide have a wide spectral range of activity compared to most of the organic sunscreen products. It is not uncommon for organic sunscreens to cause photocontact allergy, but their cosmetic acceptability is still superior to the one given by inorganic sunscreens. Recently, modern galenic approaches such as micronization and encapsulation allow the development of high-quality inorganic sunscreens. The potential systemic toxicity of organic sunscreens has lately primarily been discussed controversially in public, and several studies show contradictory results. Although a matter of debate, at present the sun protection factor (SPF) is the most reliable information for the consumer as a measure of sunscreen filter efficacy. In this context additional tests have been introduced for the evaluation of not only the protective effect against erythema but also protection against UV-induced immunological and mutational effects. Recently, combinations of UV filters with agents active in DNA repair have been introduced in order to improve photoprotection. This article reviews the efficacy of sunscreens in the prevention of epithelial and nonepithelial skin cancer, the effect on immunosuppression and the value of the SPF as well as new developments on the sunscreen market. Copyright (C) 2005 S. Karger AG, Basel

Incorporating ‘recruitment’ in matrix projection models : estimation, parameters, and the influence of model structure

Author Posting. © The Author(s), 2010. This is the author's version of the work. It is posted here by permission of Springer for personal use, not for redistribution. The definitive version was published in Journal of Ornithology 152, Suppl.2 (2012):585-595, doi:10.1007/s10336-010-0573-1.Advances in the estimation of population parameters using encounter data from marked individuals have made it possible to include estimates of the probability of recruitment in population projection models. However, the projected growth rate of the population, and the sensitivity of projected growth to changes in recruitment, can vary significantly depending upon both the structural form of the model and how recruitment is parameterized. We show that the common practices of (1) collapsing some age classes into a single, terminal ‘aggregated’ age-class, and (2) parameterizing recruitment using the proportion of recruited individuals (breeders) in a given age-class may confound analysis of age-based (Leslie) matrix projection models in some instances, relative to state-based projection models where recruited and pre-recruited individuals are treated as separate states. Failing to account for these differences can lead to misinterpretation of the relative role of recruitment in the dynamics of an age-structured population.We show that such problems can be avoided, either by structural changes to the terminal aggregated age-class in age-based models, or by using using a state-based model instead. Since all the metrics of general interest from a classical age-based matrix models are readily derived from a state-based model equivalent, this suggests there may be little reason to use the classical age-based approach in situations where recruitment is a parameter of interest

IGD Motifs, Which Are Required for Migration Stimulatory Activity of Fibronectin Type I Modules, Do Not Mediate Binding in Matrix Assembly

Picomolar concentrations of proteins comprising only the N-terminal 70-kDa region (70K) of fibronectin (FN) stimulate cell migration into collagen gels. The Ile-Gly-Asp (IGD) motifs in four of the nine FN type 1 (FNI) modules in 70K are important for such migratory stimulating activity. The 70K region mediates binding of nanomolar concentrations of intact FN to cell-surface sites where FN is assembled. Using baculovirus, we expressed wildtype 70K and 70K with Ile-to-Ala mutations in 3FNI and 5FNI; 7FNI and 9FNI; or 3FNI, 5FNI, 7FNI, and 9FNI. Wildtype 70K and 70K with Ile-to-Ala mutations were equally active in binding to assembly sites of FN-null fibroblasts. This finding indicates that IGD motifs do not mediate the interaction between 70K and the cell-surface that is important for FN assembly. Further, FN fragment N-3FNIII, which does not stimulate migration, binds to assembly sites on FN-null fibroblast. The Ile-to-Ala mutations had effects on the structure of FNI modules as evidenced by decreases in abilities of 70K with Ile-to-Ala mutations to bind to monoclonal antibody 5C3, which recognizes an epitope in 9FNI, or to bind to FUD, a polypeptide based on the F1 adhesin of Streptococcus pyogenes that interacts with 70K by the β-zipper mechanism. These results suggest that the picomolar interactions of 70K with cells that stimulate cell migration require different conformations of FNI modules than the nanomolar interactions required for assembly

Performance of random forest when SNPs are in linkage disequilibrium

<p>Abstract</p> <p>Background</p> <p>Single nucleotide polymorphisms (SNPs) may be correlated due to linkage disequilibrium (LD). Association studies look for both direct and indirect associations with disease loci. In a Random Forest (RF) analysis, correlation between a true risk SNP and SNPs in LD may lead to diminished variable importance for the true risk SNP. One approach to address this problem is to select SNPs in linkage equilibrium (LE) for analysis. Here, we explore alternative methods for dealing with SNPs in LD: change the tree-building algorithm by building each tree in an RF only with SNPs in LE, modify the importance measure (IM), and use haplotypes instead of SNPs to build a RF.</p> <p>Results</p> <p>We evaluated the performance of our alternative methods by simulation of a spectrum of complex genetics models. When a haplotype rather than an individual SNP is the risk factor, we find that the original Random Forest method performed on SNPs provides good performance. When individual, genotyped SNPs are the risk factors, we find that the stronger the genetic effect, the stronger the effect LD has on the performance of the original RF. A revised importance measure used with the original RF is relatively robust to LD among SNPs; this revised importance measure used with the revised RF is sometimes inflated. Overall, we find that the revised importance measure used with the original RF is the best choice when the genetic model and the number of SNPs in LD with risk SNPs are unknown. For the haplotype-based method, under a multiplicative heterogeneity model, we observed a decrease in the performance of RF with increasing LD among the SNPs in the haplotype.</p> <p>Conclusion</p> <p>Our results suggest that by strategically revising the Random Forest method tree-building or importance measure calculation, power can increase when LD exists between SNPs. We conclude that the revised Random Forest method performed on SNPs offers an advantage of not requiring genotype phase, making it a viable tool for use in the context of thousands of SNPs, such as candidate gene studies and follow-up of top candidates from genome wide association studies.</p

Spacelike Singularities and Hidden Symmetries of Gravity

We review the intimate connection between (super-)gravity close to a spacelike singularity (the "BKL-limit") and the theory of Lorentzian Kac-Moody algebras. We show that in this limit the gravitational theory can be reformulated in terms of billiard motion in a region of hyperbolic space, revealing that the dynamics is completely determined by a (possibly infinite) sequence of reflections, which are elements of a Lorentzian Coxeter group. Such Coxeter groups are the Weyl groups of infinite-dimensional Kac-Moody algebras, suggesting that these algebras yield symmetries of gravitational theories. Our presentation is aimed to be a self-contained and comprehensive treatment of the subject, with all the relevant mathematical background material introduced and explained in detail. We also review attempts at making the infinite-dimensional symmetries manifest, through the construction of a geodesic sigma model based on a Lorentzian Kac-Moody algebra. An explicit example is provided for the case of the hyperbolic algebra E10, which is conjectured to be an underlying symmetry of M-theory. Illustrations of this conjecture are also discussed in the context of cosmological solutions to eleven-dimensional supergravity.Comment: 228 pages. Typos corrected. References added. Subject index added. Published versio

A Two-Stage Random Forest-Based Pathway Analysis Method

Pathway analysis provides a powerful approach for identifying the joint effect of genes grouped into biologically-based pathways on disease. Pathway analysis is also an attractive approach for a secondary analysis of genome-wide association study (GWAS) data that may still yield new results from these valuable datasets. Most of the current pathway analysis methods focused on testing the cumulative main effects of genes in a pathway. However, for complex diseases, gene-gene interactions are expected to play a critical role in disease etiology. We extended a random forest-based method for pathway analysis by incorporating a two-stage design. We used simulations to verify that the proposed method has the correct type I error rates. We also used simulations to show that the method is more powerful than the original random forest-based pathway approach and the set-based test implemented in PLINK in the presence of gene-gene interactions. Finally, we applied the method to a breast cancer GWAS dataset and a lung cancer GWAS dataset and interesting pathways were identified that have implications for breast and lung cancers

Acetylsalicylic acid as an adjuvant therapy for schizophrenia

BACKGROUND: Findings from both epidemiological and basic research point to the possibility that NSAIDS impede the deterioration in schizophrenia. METHODS: To study the efficacy of acetylsalicylic acid we will perform a randomized placebo controlled double-blind add-on trial of 80 inpatients and outpatients with schizophrenia, schizophreniform or schizoaffective disorder. Patients will be 1:1 randomized to either 3 months 1000 mg acetylsalicylic acid per day or 3 months placebo, in addition to their regular antipsychotic treatment. All patients will receive pantoprazole treatment for gastroprotection. The outcomes of this study are 3-month change in psychotic and negative symptom severity, cognitive function, and several immunological parameters. This trial may (1) yield a new (adjuvant) therapy for schizophrenia and (2) add to the knowledge on the pathogenesis of this major psychiatric disorder